Stefan Hegselmann

649 total citations · 2 hit papers
18 papers, 233 citations indexed

About

Stefan Hegselmann is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems and Management. According to data from OpenAlex, Stefan Hegselmann has authored 18 papers receiving a total of 233 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Molecular Biology and 7 papers in Information Systems and Management. Recurrent topics in Stefan Hegselmann's work include Biomedical Text Mining and Ontologies (7 papers), Scientific Computing and Data Management (7 papers) and Semantic Web and Ontologies (4 papers). Stefan Hegselmann is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Scientific Computing and Data Management (7 papers) and Semantic Web and Ontologies (4 papers). Stefan Hegselmann collaborates with scholars based in Germany, United Kingdom and China. Stefan Hegselmann's co-authors include Hunter Lang, Monica Agrawal, Yoon Kim, David Sontag, Martin Dugas, Julian Varghese, Philipp Neuhaus, Benjamin Wild, Roland Eils and Sarah Sandmann and has published in prestigious journals such as Nature Medicine, Nature Communications and BMC Medical Informatics and Decision Making.

In The Last Decade

Stefan Hegselmann

17 papers receiving 221 citations

Hit Papers

Large language models are few-shot clinical information e... 2022 2026 2023 2024 2022 2025 40 80 120
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Large language models are few-shot clinical information extractors
    2022 142 citations Monica Agrawal, Stefan Hegselmann et al. profile →
  2. Benchmark evaluation of DeepSeek large language models in clinical decision-making
    2025 23 citations Sarah Sandmann, Stefan Hegselmann et al. Nature Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stefan Hegselmann Germany 6 132 53 43 30 29 18 233
Dylan Hall United States 5 157 1.2× 31 0.6× 33 0.8× 18 0.6× 57 2.0× 7 247
Joseph C. Nichols United States 3 139 1.1× 27 0.5× 32 0.7× 16 0.5× 51 1.8× 3 218
Andre Quina United States 4 147 1.1× 31 0.6× 36 0.8× 17 0.6× 63 2.2× 7 265
Deepika Gopukumar United States 4 97 0.7× 30 0.6× 66 1.5× 27 0.9× 85 2.9× 6 318
Blagoj Ristevski North Macedonia 5 52 0.4× 35 0.7× 55 1.3× 32 1.1× 60 2.1× 22 266
Lewis J. Frey United States 11 117 0.9× 17 0.3× 113 2.6× 23 0.8× 49 1.7× 41 340
Thiagarajan Raghuram United States 3 71 0.5× 34 0.6× 29 0.7× 28 0.9× 129 4.4× 3 290
Alexander Bartschke Germany 3 40 0.3× 27 0.5× 35 0.8× 26 0.9× 47 1.6× 6 159
Kevin J. Peterson United States 7 132 1.0× 28 0.5× 91 2.1× 10 0.3× 44 1.5× 20 204
Duane Bender Canada 3 95 0.7× 22 0.4× 61 1.4× 53 1.8× 127 4.4× 5 322

Countries citing papers authored by Stefan Hegselmann

Since Specialization
Citations

This map shows the geographic impact of Stefan Hegselmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefan Hegselmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Hegselmann more than expected).

Fields of papers citing papers by Stefan Hegselmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefan Hegselmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefan Hegselmann. The network helps show where Stefan Hegselmann may publish in the future.

Co-authorship network of co-authors of Stefan Hegselmann

This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Hegselmann. A scholar is included among the top collaborators of Stefan Hegselmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stefan Hegselmann. Stefan Hegselmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Steinfeldt, Jakob, Benjamin Wild, Thore Buergel, et al.. (2025). Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats. Nature Communications. 16(1). 585–585. 3 indexed citations
2.
Sandmann, Sarah, et al.. (2025). Benchmark evaluation of DeepSeek large language models in clinical decision-making. Nature Medicine. 31(8). 2546–2549. 23 indexed citations breakdown →
3.
Hegselmann, Stefan, Philipp Neuhaus, Michael Storck, et al.. (2024). Europe's Largest Research Infrastructure for Curated Medical Data Models with Semantic Annotations. Methods of Information in Medicine. 63(01/02). 52–61.
4.
Agrawal, Monica, Stefan Hegselmann, Hunter Lang, Yoon Kim, & David Sontag. (2022). Large language models are few-shot clinical information extractors. 1998–2022. 142 indexed citations breakdown →
5.
Hegselmann, Stefan, et al.. (2022). Development and validation of an interpretable 3 day intensive care unit readmission prediction model using explainable boosting machines. Frontiers in Medicine. 9. 960296–960296. 9 indexed citations
6.
Hegselmann, Stefan, et al.. (2021). An Open-Source, Standard-Compliant, and Mobile Electronic Data Capture System for Medical Research (OpenEDC): Design and Evaluation Study. JMIR Medical Informatics. 9(11). e29176–e29176. 4 indexed citations
7.
Hegselmann, Stefan, Michael Storck, Philipp Neuhaus, et al.. (2021). Pragmatic MDR: a metadata repository with bottom-up standardization of medical metadata through reuse. BMC Medical Informatics and Decision Making. 21(1). 160–160. 8 indexed citations
8.
Hegselmann, Stefan, et al.. (2020). An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions.. 46–79. 4 indexed citations
9.
Dugas, Martin, et al.. (2019). Compatible Data Models at Design Stage of Medical Information Systems: Leveraging Related Data Elements from the MDM Portal. Studies in health technology and informatics. 264. 113–117. 5 indexed citations
10.
Neuhaus, Philipp, et al.. (2019). Semantically Annotated Metadata: Interconnecting Samply.MDR and MDM-Portal. Studies in health technology and informatics. 267. 86–92. 3 indexed citations
11.
Hegselmann, Stefan, et al.. (2018). Reproducible Survival Prediction with SEER Cancer Data. 49–66. 3 indexed citations
12.
Varghese, Julian, et al.. (2018). CDEGenerator: an online platform to learn from existing data models to build model registries. Clinical Epidemiology. Volume 10. 961–970. 7 indexed citations
13.
Hegselmann, Stefan, et al.. (2018). A Web Service to Suggest Semantic Codes Based on the MDM-Portal. Studies in health technology and informatics. 253. 35–39. 5 indexed citations
14.
Soto‐Rey, Iñaki, Philipp Neuhaus, Philipp Bruland, et al.. (2018). Standardising the Development of ODM Converters: The ODMToolBox. Studies in health technology and informatics. 247. 231–235. 4 indexed citations
15.
Storck, Michael, et al.. (2017). Automated Transformation of CDISC ODM to OpenClinica. Studies in health technology and informatics. 243. 95–99. 3 indexed citations
16.
Hegselmann, Stefan, et al.. (2017). Automatic Conversion of Metadata from the Study of Health in Pomerania to ODM. Studies in health technology and informatics. 236. 88–96. 5 indexed citations
17.
Doetsch, Patrick, Hermann Ney, Stefan Hegselmann, & Ralf Schlüter. (2016). Inverted HMM - a Proof of Concept. Neural Information Processing Systems. 3 indexed citations
18.
Grädel, Erich & Stefan Hegselmann. (2016). Counting in Team Semantics. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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